Side lobe free medical ultrasonic imaging with application to assessing side lobe suppression filter

When focusing using an ultrasonic transducer array, a main lobe is formed in the focal region of an ultrasound field, but side lobes also arise around the focal region due to the leakage. Since the side lobes cannot be completely eliminated in the focusing process, they are responsible for subsequent ultrasound image quality degradation. To improve ultrasound image quality, a signal processing strategy to reduce side lobes is definitely in demand. To this end, quantitative determination of main and side lobes is necessary. We propose a theoretically and actually error-free method of exactly discriminating and separately computing the main lobe and side lobe parts in ultrasound image by computer simulation. We refer to images constructed using the main and side lobe signals as the main and side lobe images, respectively. Since the main and side lobe images exactly represent their main and side lobe components, respectively, they can be used to evaluate ultrasound image quality. Defining the average brightness of the main and side lobe images, the conventional to side lobe image ratio, and the main to side lobe image ratio as image quality metrics, we can evaluate image characteristics in speckle images. The proposed method is also applied in assessing the performance of side lobe suppression filtering. We show that the proposed method may greatly aid in the evaluation of medical ultrasonic images using computer simulations, albeit lacking the use of actual experimental data.

Estimation and suppression of side lobes in medical ultrasound imaging systems

This paper estimates the side lobe levels from the received echo data, and proposes and compares three types of filters that can be used to suppress them in an ultrasound image. Ultrasound echo signals from the offaxis scatterers can be modeled as a sinusoidal wave whose spatial frequency in the lateral direction of a transducer array varies as a function of the incident angle. The received channel data waveform due to side lobes have a spatial frequency of an integer plus a half. Doubling the length of the channel data by appending zeros and taking the discrete Fourier transform of the elongated data makes the spatial frequency of the channel data due to side lobes become an integer. Thus, it is possible to estimate the complex amplitude of the side lobes. Adding together all the channel data of the estimated side lobes, we can obtain the side lobe levels present in ultrasound field characteristics. We define the summed value as a quality factor that is used as a parameter of side lobe suppression filters. Computer simulations as well as experiments on wires in a water tank and a cyst phantom show that the proposed filters are very effective in reducing side lobe levels and that the amount of computation is smaller than that of the minimum variance beamforming method while showing comparable performance. A method of estimating and suppressing side lobes in an ultrasound image is presented, and the performance of the proposed filters is found to be viable against the conventional B-mode imaging and minimum variance beamforming methods.